A Review on Performance of Self-Compacting Concrete – Use of Mineral Admixtures and Steel Fibres with Artificial Neural Network Application

[Display omitted] •This review article helps to summarize the current state of various SCCs.•Use of steel fibres along with mineral admixtures enhances the performance of SCC.•Combination of hybrid fibres in SCC enhances the flexural strength and performance towards durability.•Number of pores in SC...

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Veröffentlicht in:Construction & building materials 2020-11, Vol.261, p.120215, Article 120215
Hauptverfasser: Ramkumar, K.B., Kannan Rajkumar, P.R., Noor Ahmmad, Shaik, Jegan, M.
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Sprache:eng
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Zusammenfassung:[Display omitted] •This review article helps to summarize the current state of various SCCs.•Use of steel fibres along with mineral admixtures enhances the performance of SCC.•Combination of hybrid fibres in SCC enhances the flexural strength and performance towards durability.•Number of pores in SCC is less when the fluidity of the concrete is better.•The Error level prediction in ANN is very less compared to linear regression. Self-compacting concrete(SCC) has high value for deformability and segregation resistance, moderateviscosity and smaller yield stress. When pouring the SCC, the mix possesses the distinctive practical features such as - it is easily flown around and within the formwork. Using the ingredients of normal concrete, the SCC is produced. Cementitious materials are adopted for replacing the SCC cement content using agricultural products and industrial waste materials. For optimizing the material contained in SCC to obtain effective performance many machine learning approaches are implemented. This paper focuses on undertaking a review of SCC along with fibre reinforcement and cement replacement materials along with the role of ANN in predicting the optimum composition of SCC. The prime objective is on compiling the various literature available for understanding different SCC properties in the hardened and fresh state and also when these fibres and cement replacement items are introduced.
ISSN:0950-0618
1879-0526
DOI:10.1016/j.conbuildmat.2020.120215